European Journal of Wood and Wood Products最新文献

Wood panels play a key role in the industrialization of construction, combining technological and sustainable characteristics being associated with a possible lower environmental impact related to carbon fixation and the replacement of non-renewable materials. The growing global consumption of OSB (Oriented Strand Board) panels highlights their relevance and consolidation in the market. Therefore, to ensure the safe application of these composites as construction components, viable alternatives to traditional raw materials must be explored to meet regulatory and technological requirements. In this context, OSB panels were produced using eucalyptus wood which is a fast-growing reforestation hardwood, and castor oil polyurethane adhesive, which is derived from renewable sources. This preliminary study evaluated the physical and mechanical properties of the panels produced, including density (D), moisture content (MC), swelling in thickness − 24 h (TS), water absorption (WA), modulus of elasticity (MOE) and modulus of strength in bending (MOR) in both parallel (p.a.) and perpendicular directions (pe), internal bond (IB), and Resistance to axial withdrawal of screws in face and edge (PS-s and PS-t). The average results were compared with the use classes of Standard EN 300:2006, demonstrating that the panels meet OSB/4 classification (heavy-duty load-bearing boards for humid conditions) and also with literature. Notably, the mechanical properties exceeded standard requirements by 57% for MOE-pa, 79% for MOR-pa, 39% for MOE-pe, 80% for MOR-pe, 189% for IB, 38% for PS-s, and 172% for PS-t, confirming their production viability and excellent structural performance.

According to the Eurocode standards, advanced numerical models or the reduced cross-section method can be used to determine the mechanical resistance of timber structures under fire conditions. The method assumes a rectangular effective cross-section with full strength and stiffness and the cross-section of effective thickness without strength and stiffness after fire exposure. The effective thickness is the sum of the charring thickness and the zero-strength layer thickness, which are specified in the standards only for standard fire exposure. In the present paper, the analyses are combined with the reduced cross-section method and numerical fire, hygro-thermal and mechanical models to determine the charring thickness, zero-strength layer thickness and effective thickness of a simply supported timber beam under bending exposed to different natural fires. The results show that the three thicknesses increase with fire duration until the end values are reached at which the timber beam can withstand a prescribed natural fire. The end values for the charring thickness are between 18.2 mm and 72.1 mm, for the zero-strength layer thickness between 14.9 mm and 27.4 mm and for the effective thickness between 39.9 mm and 89.9 mm. The results also show that the end values of the charring thickness and the effective thickness depend on the maximum gas temperature. The end values of the zero-strength layer thickness depend on the linear cooling rate. Simple linear equations are proposed to account for these dependencies. Piecewise linear equations are also proposed to describe the temporal development of the three thicknesses.

To improve wood utilization in the field of construction engineering, a fiber reinforced recycled composite wood was successfully prepared using waste wood, polypropylene and polyester fiber in this work. The polypropylene was utilized as a hot melt adhesive and the fiber was employed as a lashing bundle, which both enhance the mechanical property of the composite wood. The flexure performance of the composite wood was tested and its constitutive model was established for analyzing its stress–strain characteristics. The results show that the waste wood combined with polypropylene and fiber can be recycled as a serviceable composite, and its flexural strength and flexural stiffness were elevated by approximately 54% and 20%, respectively. The strength defect in the tension zone of the recycled wood was improved and its compression zone can enter the plastic stage thus improving its force coordination. The constitutive model of the composite wood was established based on the Hill Criterion and 3D-Hashin Criterion. The simulation method proposed can accurately predict the mechanical behavior and failure process of composite wood during bending, and its yield trend and damage process are close to actual experiments, which was used to reveal the strengthening mechanism of polypropylene and fiber on the wood.

The objective of this work was to investigate the selected properties of particleboard (PB) containing waste rubber – a mixture of carpets and isolators (GWR) and tires (GWT) from discarded automobiles. Mechanical (tensile strength (IB), bending strength (BS), physical (water absorption (WA), thickness swelling (TS) after 2 and 24 h of immersion), chemical (volatile compounds - VOC using GC-MS method), thermo-physical (thermal conductivity and diffusivity, specific heat capacity) and sound absorption coefficient were analyzed. In addition, a density profile and microscopic analysis of the particleboards were performed. The addition of 10% rubber to the PB either maintains the IB or improves the BS of the composite. The best results for WA after 24 h (97.94%) and TS after 24 h (30.74%) were achieved for composites containing tire granulates. For this reason, these PBs are the most suitable for utilization in areas with higher humidity. Adding 20% of GWR to PB decreased the total content of VOC emissions by 85% so it can be stated that the rubber probably acts as a VOC sorbent. Control PBs had significantly lower thermal conductivity and diffusivity, and comparable specific heat capacity values than PBs containing GWR and GWT. The best sound insulation properties were obtained for PBs containing 20% of GWR. Microscopic analysis pointed to greater GWT and GWR contents resulting in higher C content in the PB. All PBs containing GWR have a higher mean density compared to that of control, ranging from 597 kg·m⁻³ to 615 kg·m⁻³. On the other hand, PB containing GWT had comparable or lower density values.

In wood–plastic composites (WPCs) milling, achieving optimal material removal rates and surface roughness levels are critical objectives. In this study, WPCs milling experiments were conducted, and a back propagation (BP) neural network was applied to develop a predictive model for surface roughness. A geometric method was used to derive the calculation formula for the material removal rate. Subsequently, a multi-objective approach was adopted to determine the optimal combination of control factors, including spindle speed n, feed rate U, milling depth h, for WPCs milling. The findings indicate that an increase in spindle speed reduced surface roughness, whereas higher feed speed and milling depth resulted in increased surface roughness. Variance analysis revealed that milling depth had the greatest impact on surface roughness, contributing 34.66%, followed by feed speed at 30.77% contribution and spindle speed at 30.55% contribution. A BP prediction model for surface roughness was established with high accuracy, exhibiting a maximum error of 4.89%. Furthermore, a multi-objective particle swarm optimization algorithm was applied to optimize the objectives of minimizing surface roughness and maximizing material removal rate. Based on the obtained Pareto front, the milling parameter combination of n = 12,000 r/min, U = 3.23 m/min, and h = 0.4 mm is recommended for roughing. For semi-finishing, the optimal parameters are n = 12,000 r/min, U = 4.76 m/min, and h = 0.4 mm. For finishing, the suitable combination is n = 12,000 r/min, U = 6 m/min, and h = 0.72 mm. Experimental verification demonstrated a maximum predictive error of 16.87%, confirming the feasibility of the multi-objective optimization approach.

Plywood is a valuable material that offers superior properties compared to solid wood. However, like solid wood, its poor flammability limits its suitability for various applications. This study investigates the impact of distinct types of fire retardants (FRs), designated as B, P, and U, as well as various application techniques—roller coating, spraying, and impregnation—on the bond strength and fire performance of aspen and birch veneers. A lap shear test (LST) was conducted to compare the bond strength of veneers bonded with a newly developed lignin-substituted phenolic formaldehyde (LPF) resin against a conventional formaldehyde resin (PF) to evaluate the effects of FR treatments. The results indicated that FR retention was significantly higher with impregnation and, overall, with aspen veneers than birch, except for aspen veneers treated using the spraying method with P-FR. The P-FR exhibited strong and consistent performance with birch veneers, irrespective of the treatment method. Notably, P-FR roller-coated aspen, with an FR retention of 9.5% and an ignition time of 11 s, demonstrated the best overall reaction to fire performance. With a basic protection duration of 52 s and a thermal decay time of 157 s, this combination demonstrated improved thermal resistance. The LST further revealed that FR treatments significantly impacted birch veneers, which experienced a 30–48% decrease in shear strength with PF resin relative to untreated veneers. The LPF resin was incompatible with birch veneers when treated with P-FR formulated from a protic ionic liquid. For aspen, the overall decrease in shear strength was 40%, but with B- and U-FR treatments, the reductions reached 38% and 50%, respectively—much higher than the decreases observed in birch (25% and 37%) relative to control samples. These findings provide valuable insights into the effects of fire retardants on new resins, though further research is necessary for comprehensive validation.

Composite materials, such as engineered wood products (EWPs), are favored for their stability, durability, and uniform mechanical properties, making them a potential way to valorize hardwood species. Therefore, this article aims to present a decade review of hardwood composites and their developments. The methodology of this review was divided into three main parts. First, a search for peer-reviewed articles on EWPs published between 2012 and 2023 was conducted using the Web of Science (WOS) database. Second, the data extracted from the WOS database were analyzed using the Virtual Operating System (VOS) viewer and a bibliometric approach. Third, selected peer-reviewed articles were systematically reviewed and included in this study, and their main findings were presented. The reviewed documents showed that hardwood composites are favored for their stability, durability, and uniform mechanical properties, which make them attractive for various engineering applications. Some key findings from the review include the potential of Yellow Birch to enhance wood-plastic composites by improving flexural strength and reducing flammability. Eucalyptus nanofibers have shown promise in enhancing the mechanical performance of composite mixtures. Hybrid poplar has been identified for its suitability in cross-laminated timber (CLT) products as they meet and exceed the shears and bending strength required by ANSI/APA PRG-320. Moreover, I-joists made from hardwood residues exhibit comparable mechanical performance to commercial counterparts. The review underscores the need for continued research and development to foster wider adoption of these valuable materials.

There is growing interest in developing natural wood preservatives, particularly in response to the escalating challenges posed by environmental degradation. Caffeine is a bio-based preservative that improves decay resistance of treated wood, however it is also sensitive to leaching from wood when exposed to water. Combining chitosan-caffeine formulations limits the leaching of caffeine from impregnated wood, thereby increasing its resistance even under outdoor conditions. This research aimed to evaluate the properties of wood impregnated with chitosan-caffeine formulations, focusing on wettability (contact angle measurement), mechanical properties (bending strength), and sorption behavior. The contact angle measurement revealed that wood treated with chitosan and chitosan-caffeine formulations exhibited an improvement in water resistance compared to untreated wood and wood treated with caffeine alone. However, this resistance showed only for short-term application. Both caffeine and chitosan treatments reduced the equilibrium moisture content during adsorption and desorption phases in the relative air humidity range from 0 to 0.95. The application of chitosan-caffeine formulations for wood impregnation resulted in a reduction in equilibrium moisture content, as well as hygroscopicity of the treated wood. Treatment with all formulation variants had no effect on the mechanical parameters, including modulus of elasticity and modulus of rupture. In addition, FTIR results indicated that both caffeine and chitosan interact with wood components. These findings suggest that chitosan-caffeine formulations are promising as natural wood preservatives, offering an improved hygroscopicity while maintaining the mechanical properties of the treated wood.

Previous studies on the hydrothermal liquefaction (HTL) of biomass have primarily focused on bio-oil production, overlooking the significant hydrochar by-product. In this work, the HTL of beech wood, soda lignin, and black liquor was performed at temperatures of 300 °C and 350 °C for 20 min. The effect of temperature and biomass type on hydrochar yields and properties was thoroughly investigated. The mass yields of the hydrochars varied between 25.92 wt% and 32.70 wt%. An increase in temperature from 300 °C to 350 °C led to a decrease in hydrochar mass yields. The carbon yield was found to be highest (51 wt%) at 300 °C using beech wood. The highest heating value, 30.97 MJ/kg, was obtained with hydrochar derived from soda lignin at 300 °C. Solid-state carbon NMR demonstrated that the hydrochars derived from black liquor contain condensed aromatic structures. Both the type of biomass and temperature significantly influenced the characteristics of the resulting hydrochar. This research demonstrates that hydrochar holds promise as a solid biofuel due to its advantageous energy content and carbon yield, highlighting its potential for sustainable energy applications.

Moisture damage poses a significant threat to building envelopes, leading to mould growth and reduced thermal insulation, thereby affecting indoor air quality and human health. Wood, as a promising eco-friendly building material, is highly sensitive to moisture, making hygrothermal monitoring of wooden walls essential. However, sensors used for monitoring are prone to failures, and the high maintenance and replacement costs make long-term monitoring challenging. Therefore, this study combines short-term monitoring data from sensors within the wall with outdoor climate data to predict long-term hygrothermal responses using machine learning (ML) models after monitoring ended. The ML model, which consists of a one-dimensional convolutional neural network (1D-CNN) and a long short-term memory (LSTM) network, was trained using two years of monitoring data and outdoor climate data from a four-story timber-framed office building. Subsequently, the SHapley Additive exPlanation (SHAP) method was employed to interpret the impact of each feature on the model’s predictions. Finally, the ML model was used to predict the hygrothermal responses inside the wall for three years after monitoring ended, and the mould growth risk for walls in different orientations was assessed using the predicted data. The study found that during the monitoring period, 97.9% of the test points showed no mould growth risk, and 2.1% showed low risk, indicating the wall assembly strong adaptability to Tianjin’s climate. The ML model performed excellently in predicting the temperature inside the wall, with an average R² of 0.952, and showed moderate accuracy in predicting relative humidity, with an average R² of 0.805. Predictions for three years after monitoring ends indicated that the maximum mould index for north-oriented walls reached 1.06 during heavy rainfall periods, posing a potential low risk. The method proposed in this study allows for long-term assessment by updating outdoor climate data, effectively utilizing data from sensors during short-term monitoring periods and serving as a cost-effective alternative after monitoring ends.